Detection of systemic cardiovascular illnesses and cardiometabolic risk factors with machine learning and optical coherence tomography angiography: a pilot study.

This study demonstrates the strength of ML to identify the presence cardiometabolic factors, in particular hyperlipidaemia, in high-resolution 3 × 3 mm OCTA scans. Early detection of risk factors prior to a clinically significant event, will assist in preventing adverse outcomes for people.